Abstract: Elastic computing is an optimization framework that combines standard application code with specialized elastic functions and corresponding optimization tools. The elastic functions provide a knowledge-base of implementation alternatives and parallelization strategies for a given function. When an application calls an elastic function, the elastic computing tools analyze available devices and resources (e.g., cores, GPUs, FPGAs, etc.) and current run-time parameters, and then transparently select from numerous pre-analyzed implementation possibilities to optimize for performance, power, energy, size, or any combination of these goals.

Abstract: Elastic computing is an optimization framework that combines standard application code with specialized elastic functions and corresponding optimization tools. The elastic functions provide a knowledge-base of implementation alternatives and parallelization strategies for a given function. When an application calls an elastic function, the elastic computing tools analyze available devices and resources (e.g., cores, GPUs, FPGAs, etc.) and current run-time parameters, and then transparently select from numerous pre-analyzed implementation possibilities to optimize for performance, power, energy, size, or any combination of these goals.

Abstract: A warp processor includes a microprocessor, profiler, dynamic partitioning module, and warp configurable logic architecture. The warp processor initially executes a binary for an application entirely on the microprocessor, the profiler monitors the execution of the binary to detect its critical code regions, and the dynamic partitioning module partitions the binary into critical and non-critical code regions, re-implements the critical code regions in the configurable logic, and then transforms the binary so that it accesses the configurable logic rather than execute the critical code regions.